LangChain
14 articles tagged with this topic
Agent 的推理方式不 止一种，但大多数人搞混了它们 的层级关系
ReAct, Reflexion, and Router aren't alternatives —they operate at different layers. Picking the wrong level means costly rebuilds.
AI 助手「自己会 想下一步」背后，藏着三层架构——读 懂它，你才知道它什么时候会失控
Most AI coding assistants run on a three-layer nested architecture. Understanding it tells you exactly when and why AI loses control.
Hermes Agent Framework Hits 85K Stars With Self-Evolving Memory
Nous Research's Hermes Agent, open-sourced in February 2026 , reaches 85K GitHub stars with a four-layer memory architecture and runtime skill accumu
RAG Migration From Self-Hosted to API Cuts Costs 97%
A Chinese SaaS firm cut monthly AI infra costs from ¥80,000 to under ¥2,000 by ditching 4x A100s for DeepSeek API.
OpenClaw Nanobot Architecture: AI Agent Design Pattern Analysis
OpenClaw's Nanobot pattern reaches 200K GitHub stars as devs dissect its declarative, composable AI agent design.
Cirrus Labs Acquired by OpenAI: What This Means for Solo Builders and AI Tooling
Cirrus Labs joins OpenAI, signaling a shift in AI infrastructure. Analyze the implications for indie hackers, open-source alternatives, and how to piv
LangChain-Chroma High-Concurrency Architecture: Beyond Basic RAG
How to fix write blocking, query latency spikes, and OOM errors when scaling Chroma from prototype to production.
Vector DBs for Solo Builders: Chroma, FAISS & Pinecone with LangChain
Compare Chroma, FAISS, Pinecone, and Milvus for LangChain RAG apps — with selection criteria for one-person teams.
LLM Cognitive Architecture: From Rule-Based to Autonomous Agents
A technical breakdown of four-layer LLM agent architecture with Python code using LangChain and LangGraph.
LCEL in Practice: Engineering 4 Core LangChain Pipeline Patterns
How to structure LangChain LCEL chains for linear, routing, RAG, and agent workflows in production.
LangChain Vector Embeddings: From Basics to RAG Implementation
Practical guide to LangChain embeddings using OpenAI, HuggingFace, and local models for semantic search and RAG pipelines.
Building a Maintainable Prompt Layer for Enterprise RAG Systems
Replace string-concatenated prompts with LangChain's ChatPromptTemplate and PipelinePromptTemplate for scalable enterprise knowledge bases.
LangChain Document Loading and Text Splitting for RAG Pipelines
How to load PDFs, Word, HTML, and Markdown files in LangChain and split them for RAG applications.
LangChain Runnable: The Interface That Makes AI Pipelines Maintainable
Why LangChain's Runnable protocol transforms scattered model calls into composable, maintainable AI workflows.